text: # coding: utf8
  from __future__ import unicode_literals
  
  from spacy.lang.en import English
  from spacy.util import minibatch, compounding
  import pytest
  
  
  @pytest.mark.filterwarnings("ignore::UserWarning")
  def test_issue4348():
      """Test that training the tagger with empty data, doesn't throw errors"""
  
      TRAIN_DATA = [("", {"tags": []}), ("", {"tags": []})]
  
      nlp = English()
      tagger = nlp.create_pipe("tagger")
      nlp.add_pipe(tagger)
  
      optimizer = nlp.begin_training()
      for i in range(5):
          losses = {}
          batches = minibatch(TRAIN_DATA, size=compounding(4.0, 32.0, 1.001))
          for batch in batches:
              texts, annotations = zip(*batch)
              nlp.update(texts, annotations, sgd=optimizer, losses=losses)
  